scholarly journals Modelling African biomass burning emissions and the effect of spatial resolution

2019 ◽  
Author(s):  
Dave van Wees ◽  
Guido R. van der Werf
Keyword(s):  
Spatial Resolution ◽  
Input Data ◽  
Large Scale ◽  
Sub Saharan Africa ◽  
Fuel Load ◽  
Burned Area ◽  
Fire Emissions ◽  
Continental Scale ◽  
Coarse Resolution ◽  
The Impact

Abstract. Large-scale fire emission estimates may be influenced by the spatial resolution of the model and input datasets used. Especially in areas with relatively heterogeneous land cover, a coarse model resolution might lead to substantial errors in estimates. In this paper, we developed a model using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations of burned area and vegetation characteristics to study the impact of spatial resolution on modelled fire emission estimates. We estimated fire emissions for sub-Saharan Africa at 500-meter spatial resolution (native MODIS burned area) for the 2002–2017 period, using a simplified version of the Global Fire Emissions Database (GFED) modelling framework, and compared this to model runs at a range of coarser resolutions (0.050°, 0.125°, 0.250°). We estimated fire emissions of 0.68 PgC yr−1 at 500-meter resolution and 0.82 PgC yr−1 at 0.25° resolution; a difference of 24 %. At 0.25° resolution, our model results were relatively similar to GFED4, which also runs at 0.25° resolution, whereas our 500-meter estimates were substantially lower. We found that lower emissions at finer resolutions are mainly the result of reduced representation errors when comparing modelled estimates of fuel load and consumption to field measurements, as part of the model calibration. Additional errors stem from the model simulation at coarse resolution and lead to an additional 0.02 PgC yr−1 difference in estimates. These errors exist due to the aggregation of quantitative and qualitative model input data; the average- or majority- aggregated values are propagated in the coarse resolution simulation and affect the model parameterization and the final result. We identified at least three error mechanisms responsible for the differences in estimates between 500-meter and 0.25° resolution simulations, besides those stemming from representation errors in the calibration process, namely: 1. biome misclassification leading to errors in parameterization, 2. errors due to the averaging of input data and the associated reduction in variability, and 3. a temporal mechanism related to the aggregation of burned area in particular. Even though these mechanisms largely neutralized each other and only modestly affect estimates at a continental scale, they lead to substantial error at regional scales with deviations up to a factor 4, and may affect large-scale estimates differently for other continents. These findings could prove valuable in improving coarse resolution models and suggest the need for increased spatial resolution in global fire emission models.

scholarly journals Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED)

2019 ◽  
Vol 12 (11) ◽  
pp. 4681-4703
Author(s):  
Dave van Wees ◽  
Guido R. van der Werf
Keyword(s):  
Spatial Resolution ◽  
Input Data ◽  
Large Scale ◽  
Sub Saharan Africa ◽  
Fuel Load ◽  
Burned Area ◽  
Fire Emissions ◽  
Continental Scale ◽  
Coarse Resolution ◽  
The Impact

Abstract. Large-scale fire emission estimates may be influenced by the spatial resolution of the model and input datasets used. Especially in areas with relatively heterogeneous land cover, a coarse model resolution might lead to substantial errors in estimates. We developed a model using MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations of burned area and vegetation characteristics to study the impact of spatial resolution on modelled fire emission estimates. We estimated fire emissions for sub-Saharan Africa at 500 m spatial resolution (native MODIS burned area) for the 2002–2017 period, using a simplified version of the Global Fire Emissions Database (GFED) modelling framework, and compared this to model runs at a range of coarser resolutions (0.050, 0.125, 0.250∘). We estimated fire emissions of 0.68 Pg C yr−1 at 500 m resolution and 0.82 Pg C yr−1 at 0.25∘ resolution; a difference of 24 %. At 0.25∘ resolution, our model results were relatively similar to GFED4, which also runs at 0.25∘ resolution, whereas our 500 m estimates were substantially lower. We found that lower emissions at finer resolutions are mainly the result of reduced representation errors when comparing modelled estimates of fuel load and consumption to field measurements, as part of the model calibration. Additional errors stem from the model simulation at coarse resolution and lead to an additional 0.02 Pg C yr−1 difference in estimates. These errors exist due to the aggregation of quantitative and qualitative model input data; the average- or majority- aggregated values are propagated in the coarse-resolution simulation and affect the model parameterization and the final result. We identified at least three error mechanisms responsible for the differences in estimates between 500 m and 0.25∘ resolution simulations, besides those stemming from representation errors in the calibration process, namely (1) biome misclassification leading to errors in parameterization, (2) errors due to the averaging of input data and the associated reduction in variability, and (3) a temporal mechanism related to the aggregation of burned area in particular. Even though these mechanisms largely neutralized each other and only modestly affect estimates at a continental scale, they lead to substantial error at regional scales with deviations of up to a factor 4 and may affect large-scale estimates differently for other continents. These findings could prove valuable in improving coarse-resolution models and suggest the need for increased spatial resolution in global fire emission models.

scholarly journals African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data

2021 ◽  
Vol 118 (9) ◽  
pp. e2011160118
Author(s):  
Ruben Ramo ◽  
Ekhi Roteta ◽  
Ioannis Bistinas ◽  
Dave van Wees ◽  
Aitor Bastarrika ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Spatial Resolution ◽  
Carbon Emissions ◽  
Sub Saharan Africa ◽  
Burned Area ◽  
Fire Emissions ◽  
Coarse Spatial Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sub Saharan ◽  
Sentinel 2

Fires are a major contributor to atmospheric budgets of greenhouse gases and aerosols, affect soils and vegetation properties, and are a key driver of land use change. Since the 1990s, global burned area (BA) estimates based on satellite observations have provided critical insights into patterns and trends of fire occurrence. However, these global BA products are based on coarse spatial-resolution sensors, which are unsuitable for detecting small fires that burn only a fraction of a satellite pixel. We estimated the relevance of those small fires by comparing a BA product generated from Sentinel-2 MSI (Multispectral Instrument) images (20-m spatial resolution) with a widely used global BA product based on Moderate Resolution Imaging Spectroradiometer (MODIS) images (500 m) focusing on sub-Saharan Africa. For the year 2016, we detected 80% more BA with Sentinel-2 images than with the MODIS product. This difference was predominately related to small fires: we observed that 2.02 Mkm2 (out of a total of 4.89 Mkm2) was burned by fires smaller than 100 ha, whereas the MODIS product only detected 0.13 million km2 BA in that fire-size class. This increase in BA subsequently resulted in increased estimates of fire emissions; we computed 31 to 101% more fire carbon emissions than current estimates based on MODIS products. We conclude that small fires are a critical driver of BA in sub-Saharan Africa and that including those small fires in emission estimates raises the contribution of biomass burning to global burdens of (greenhouse) gases and aerosols.

scholarly journals APIFLAME v1.0: high resolution fire emission model and application to the Euro-Mediterranean region

2013 ◽  
Vol 6 (4) ◽  
pp. 5489-5551
Author(s):  
S. Turquety ◽  
L. Menut ◽  
B. Bessagnet ◽  
A. Anav ◽  
N. Viovy ◽  
...  
Keyword(s):  
High Resolution ◽  
Mediterranean Area ◽  
Emission Factors ◽  
Fuel Load ◽  
Burned Area ◽  
Emission Model ◽  
Fire Emissions ◽  
The Mediterranean ◽  
The Impact ◽  
Horizontal Grid

Abstract. This paper describes a new model for the calculation of daily, high-resolution (up to 1 km) fire emissions, developed in the framework of the APIFLAME project (Analysis and Prediction of the Impact of Fires on Air quality ModEling). The methodology relies on the classical approach, multiplying the burned area by the fuel load and the emission factors specific to the vegetation burned. Emissions can be calculated on any user-specified domain, horizontal grid, and list of trace gases and aerosols, providing input information on the burned area (location, extent) and emission factors of the targeted species are available. The strength of the proposed algorithm is its high resolution and its flexibility in terms of domain and input data (including the vegetation classification). The modification of the default values and databases proposed does not require changes in the core of the model. The code may be used for the calculation of global or regional inventories. However, it has been developed and tested more specifically for Europe and the Mediterranean area. In this region, the burning season extends from June to October in most regions, with generally small but frequent fires in Eastern Europe, Western Russia, Ukraine and Turkey, and large events in the Mediterranean area. The resulting emissions represents a significant fraction of the total yearly emissions (on average amounting to ~30% of anthropogenic emissions for PM2.5, ~20% for CO). The uncertainty on the daily carbon emissions was estimated to ~100% based on an ensemble analysis. Considering the large uncertainties on emission factors, the potential error on the emissions for the various pollutants is even larger. Comparisons to other widely used emission inventories shows good correlations but discrepancies of a factor of 2–4 on the amplitude of the emissions, our results being generally on the higher end.

scholarly journals APIFLAME v1.0: high-resolution fire emission model and application to the Euro-Mediterranean region

2014 ◽  
Vol 7 (2) ◽  
pp. 587-612 ◽  
Author(s):  
S. Turquety ◽  
L. Menut ◽  
B. Bessagnet ◽  
A. Anav ◽  
N. Viovy ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Analysis ◽  
Mediterranean Area ◽  
Emission Factors ◽  
Fuel Load ◽  
Burned Area ◽  
Emission Model ◽  
Fire Emissions ◽  
The Mediterranean ◽  
The Impact

Abstract. This paper describes a new model for the calculation of daily, high-resolution (up to 1 km) fire emissions, developed in the framework of the APIFLAME (Analysis and Prediction of the Impact of Fires on Air quality ModEling) project. The methodology relies on the classical approach, multiplying the burned area by the fuel load consumed and the emission factors specific to the vegetation burned. Emissions can be calculated on any user-specified domain, horizontal grid, and list of trace gases and aerosols, providing input information on the burned area (location, extent), and emission factors of the targeted species are available. The applicability to high spatial resolutions and the flexibility to different input data (including vegetation classifications) and domains are the main strength of the proposed algorithm. The modification of the default values and databases proposed does not require any change in the core of the model. The code may be used for the calculation of global or regional inventories. However, it has been developed and tested more specifically for Europe and the Mediterranean area. A regional analysis of fire activity and the resulting emissions in this region is provided. The burning season extends from June to October in most regions, with generally small but frequent fires in eastern Europe, western Russia, Ukraine and Turkey, and large events in the Mediterranean area. The resulting emissions represent a significant fraction of the total yearly emissions (on average amounting to ~ 30% of anthropogenic emissions for PM2.5, ~ 20% for CO). The uncertainty regarding the daily carbon emissions is estimated at ~ 100% based on an ensemble analysis. Considering the large uncertainties regarding emission factors, the potential error on the emissions for the various pollutants is even larger. Comparisons with other widely used emission inventories show good correlations but discrepancies of a factor of 2–4 in the amplitude of the emissions, our results being generally on the higher end.

scholarly journals Fire Activity and Fuel Consumption Dynamics in Sub-Saharan Africa

2018 ◽  
Vol 10 (10) ◽  
pp. 1591 ◽  
Author(s):  
Gareth Roberts ◽  
Martin Wooster ◽  
Weidong Xu ◽  
Jiangping He
Keyword(s):  
Fuel Consumption ◽  
Southern Hemisphere ◽  
Land Surface ◽  
Sub Saharan Africa ◽  
Fuel Load ◽  
Biomass Combustion ◽  
Fire Emissions ◽  
Fire Activity ◽  
Sub Saharan ◽  
The Impact

African landscape fires are widespread, recurrent and temporally dynamic. They burn large areas of the continent, modifying land surface properties and significantly affect the atmosphere. Satellite Earth Observation (EO) data play a pivotal role in capturing the spatial and temporal variability of African biomass burning, and provide the key data required to develop fire emissions inventories. Active fire observations of fire radiative power (FRP, MW) have been shown to be linearly related to rates of biomass combustion (kg s−1). The Meteosat FRP-PIXEL product, delivered in near real-time by the EUMETSAT Land Surface Analysis Satellite Applications Facility (LSA SAF), maps FRP at 3 km resolution and 15-min intervals and these data extend back to 2004. Here we use this information to assess spatio-temporal variations in fire activity across sub-Saharan Africa, and identify an overall trend of decreasing annual fire activity and fuel consumption, agreeing with the widely-used Global Fire Emissions Database (GFEDv4) based on burned area measures. We provide the first comprehensive assessment of relationships between per-fire FRE-derived fuel consumption (Tg dry matter, DM) and temporally integrated Moderate Resolution Imaging Spectroradiometer (MODIS) net photosynthesis (PSN) (Tg, which can be converted into pre-fire fuel load estimates). We find very strong linear relationships over southern hemisphere Africa (mean r = 0.96) that are partly biome dependent, though the FRE-derived fuel consumptions are far lower than those derived from the accumulated PSN, with mean fuel consumptions per unit area calculated as 0.14 kg DM m−2. In the northern hemisphere, FRE-derived fuel consumption is also far lower and characterized by a weaker linear relationship (mean r = 0.76). Differences in the parameterization of the biome look up table (BLUT) used by the MOD17 product over Northern Africa may be responsible but further research is required to reconcile these differences. The strong relationship between fire FRE and pre-fire fuel load in southern hemisphere Africa is encouraging and highlights the value of geostationary FRP retrievals in providing a metric that relates very well to fuel consumption and fire emission variations. The fact that the estimated fuel consumed is only a small fraction of the fuel available suggests underestimation of FRE by Spinning Enhanced Visible and Infrared Imager (SEVIRI) and/or that the FRE-to-fuel consumption conversion factor of 0.37 MJ kg−1 needs to be adjusted for application to SEVIRI. Future geostationary imaging sensors, such as on the forthcoming Meteosat Third Generation (MTG), will reduce the impact of this underestimation through its ability to detect even smaller and shorter-lived fires than can the current second generation Meteosat.

scholarly journals Synchronous cycles of domestic dog rabies in sub-Saharan Africa and the impact of control efforts

2007 ◽  
Vol 104 (18) ◽  
pp. 7717-7722 ◽  
Author(s):  
Katie Hampson ◽  
Jonathan Dushoff ◽  
John Bingham ◽  
Gideon Brückner ◽  
Y. H. Ali ◽  
...  
Keyword(s):  
Large Scale ◽  
Domestic Dogs ◽  
Sub Saharan Africa ◽  
Domestic Dog ◽  
Eastern Africa ◽  
Prevention Measures ◽  
Persistent Problem ◽  
Canine Rabies ◽  
Continental Scale ◽  
The Impact

Rabies is a fatal neurological pathogen that is a persistent problem throughout the developing world where it is spread primarily by domestic dogs. Although the disease has been extensively studied in wildlife populations in Europe and North America, the dynamics of rabies in domestic dog populations has been almost entirely neglected. Here, we demonstrate that rabies epidemics in southern and eastern Africa cycle with a period of 3–6 years and show significant synchrony across the region. The observed period is shorter than predictions based on epidemiological parameters for rabies in domestic dogs. We find evidence that rabies prevention measures, including vaccination, are affected by disease prevalence and show that a simple model with intervention responses can capture observed disease periodicity and host dynamics. We suggest that movement of infectious or latent animals combined with coordinated control responses may be important in coupling populations and generating synchrony at the continental scale. These findings have important implications for rabies prediction and control: large-scale synchrony and the importance of intervention responses suggest that control of canine rabies in Africa will require sustained efforts coordinated across political boundaries.

scholarly journals Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations

2015 ◽  
Vol 12 (10) ◽  
pp. 10559-10601 ◽  
Author(s):  
P. Lopez Lopez ◽  
N. Wanders ◽  
J. Schellekens ◽  
L. J. Renzullo ◽  
E. H. Sutanudjaja ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Data Assimilation ◽  
Spatial Resolution ◽  
Large Scale ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Added Value ◽  
Coarse Resolution ◽  
The Impact

Abstract. The coarse spatial resolution of global hydrological models (typically > 0.25°) limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally-tuned river models. A possible solution to the problem may be to drive the coarse resolution models with locally available high spatial resolution meteorological data as well as to assimilate ground-based and remotely-sensed observations of key water cycle variables. While this would improve the resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study we investigate the impact of assimilating streamflow and satellite soil moisture observations on the accuracy of global hydrological model estimations, when driven by either coarse- or high-resolution meteorological observations in the Murrumbidgee river basin in Australia. To this end, a 0.08° resolution version of the PCR-GLOBWB global hydrological model is forced with downscaled global meteorological data (from 0.5° downscaled to 0.08° resolution) obtained from the WATCH Forcing Data methodology applied to ERA-Interim (WFDEI) and a local high resolution gauging station based gridded dataset (0.05°). Downscaled satellite derived soil moisture (from approx. 0.5° downscaled to 0.08° resolution) from AMSR-E and streamflow observations collected from 23 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global meteorological data. Results show that the assimilation of soil moisture observations results in the largest improvement of the model estimates of streamflow. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improvement in streamflow simulations (20 % reduction in RMSE). Furthermore, results show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. We conclude that it is possible to improve PCR-GLOBWB simulations forced by coarse resolution meteorological data with assimilation of downscaled spaceborne soil moisture and streamflow observations. These improved model results are close to the ones from a local model forced with local meteorological data. These findings are important in light of the efforts that are currently done to go to global hyper-resolution modelling and can help to advance this research.

scholarly journals Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3982
Author(s):  
Giacomo Lazzeri ◽  
William Frodella ◽  
Guglielmo Rossi ◽  
Sandro Moretti
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Fire Severity ◽  
Experimental Methodology ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
The Impact ◽  
Sentinel 2

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

scholarly journals Assessing the impact of hydrodynamics on large-scale flood wave propagation – a case study for the Amazon Basin

2017 ◽  
Vol 21 (1) ◽  
pp. 117-132 ◽  
Author(s):  
Jannis M. Hoch ◽  
Arjen V. Haag ◽  
Arthur van Dam ◽  
Hessel C. Winsemius ◽  
Ludovicus P. H. van Beek ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Hydrodynamic Model ◽  
Large Scale ◽  
Hydrologic Model ◽  
Flood Events ◽  
Coupled Models ◽  
Validation Parameters ◽  
Directional Coupling ◽  
Inundation Extent ◽  
The Impact

Abstract. Large-scale flood events often show spatial correlation in neighbouring basins, and thus can affect adjacent basins simultaneously, as well as result in superposition of different flood peaks. Such flood events therefore need to be addressed with large-scale modelling approaches to capture these processes. Many approaches currently in place are based on either a hydrologic or a hydrodynamic model. However, the resulting lack of interaction between hydrology and hydrodynamics, for instance, by implementing groundwater infiltration on inundated floodplains, can hamper modelled inundation and discharge results where such interactions are important. In this study, the global hydrologic model PCR-GLOBWB at 30 arcmin spatial resolution was one-directionally and spatially coupled with the hydrodynamic model Delft 3D Flexible Mesh (FM) for the Amazon River basin at a grid-by-grid basis and at a daily time step. The use of a flexible unstructured mesh allows for fine-scale representation of channels and floodplains, while preserving a coarser spatial resolution for less flood-prone areas, thus not unnecessarily increasing computational costs. In addition, we assessed the difference between a 1-D channel/2-D floodplain and a 2-D schematization in Delft 3D FM. Validating modelled discharge results shows that coupling PCR-GLOBWB to a hydrodynamic routing scheme generally increases model performance compared to using a hydrodynamic or hydrologic model only for all validation parameters applied. Closer examination shows that the 1-D/2-D schematization outperforms 2-D for r2 and root mean square error (RMSE) whilst having a lower Kling–Gupta efficiency (KGE). We also found that spatial coupling has the significant advantage of a better representation of inundation at smaller streams throughout the model domain. A validation of simulated inundation extent revealed that only those set-ups incorporating 1-D channels are capable of representing inundations for reaches below the spatial resolution of the 2-D mesh. Implementing 1-D channels is therefore particularly of advantage for large-scale inundation models, as they are often built upon remotely sensed surface elevation data which often enclose a strong vertical bias, hampering downstream connectivity. Since only a one-directional coupling approach was tested, and therefore important feedback processes are not incorporated, simulated discharge and inundation extent for both coupled set-ups is generally overpredicted. Hence, it will be the subsequent step to extend it to a two-directional coupling scheme to obtain a closed feedback loop between hydrologic and hydrodynamic processes. The current findings demonstrating the potential of one-directionally and spatially coupled models to obtain improved discharge estimates form an important step towards a large-scale inundation model with a full dynamic coupling between hydrology and hydrodynamics.

HIV/AIDS

2020 ◽  
pp. 901-933
Author(s):  
Sarah Fidler ◽  
Timothy E.A. Peto ◽  
Philip Goulder ◽  
Christopher P. Conlon
Keyword(s):  
Large Scale ◽  
Sub Saharan Africa ◽  
People Living With Hiv ◽  
African Countries ◽  
Global Pandemic ◽  
The People ◽  
Reduce Life Expectancy ◽  
Sub Saharan ◽  
Living With Hiv ◽  
The Impact

Since its discovery in 1983, the human immunodeficiency virus (HIV) has been associated with a global pandemic that has affected more than 78 million people and caused more than 39 million deaths. Globally, 36.9 million (34.3–41.4 million) people were living with HIV at the end of 2013. An estimated 0.8% of adults aged 15–49 years worldwide are living with HIV, although the burden of the epidemic continues to vary considerably between countries and regions. Sub-Saharan Africa remains most severely affected, with nearly 1 in every 20 adults living with HIV and accounting for nearly 71% of the people living with HIV worldwide. The impact of HIV in some African countries has been sufficient to reverse population growth and reduce life expectancy into the mid-30s, although HIV incidence has declined in some of these high-prevalence countries. However, there are large-scale HIV epidemics elsewhere (e.g. India, the Russian Federation, and Eastern Europe).

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